Perceptions and Detection of AI Use in Manuscript Preparation for Academic Journals
Nir Chemaya, Daniel Martin

TL;DR
This paper explores academic perceptions of AI use in manuscript writing and evaluates detection methods, addressing the need for disclosure and the effectiveness of AI detection tools.
Contribution
It provides insights into academic attitudes towards AI disclosure and assesses the current state of AI detection in scholarly publishing.
Findings
Many academics see AI disclosure as necessary.
Detection tools vary in effectiveness.
Discussions on policy implications are ongoing.
Abstract
The emergent abilities of Large Language Models (LLMs), which power tools like ChatGPT and Bard, have produced both excitement and worry about how AI will impact academic writing. In response to rising concerns about AI use, authors of academic publications may decide to voluntarily disclose any AI tools they use to revise their manuscripts, and journals and conferences could begin mandating disclosure and/or turn to using detection services, as many teachers have done with student writing in class settings. Given these looming possibilities, we investigate whether academics view it as necessary to report AI use in manuscript preparation and how detectors react to the use of AI in academic writing.
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Explainable Artificial Intelligence (XAI)
